Search results for: data analyses

Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2023 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decisionmaking and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: Tareq Nikzad

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Since the first bank was established in 1933, Afghanistan's banking sector has seen a number of variations but hasn't been able to grow to its full potential because of the civil war. The implementation of dual banks in Afghanistan is investigated in this study in relation to the effects of inflation and interest rates. This research took data from World Bank Data (WBD) over a period of nineteen years. For the banking sector, inflation, which is the general rise in prices of goods and services over time, presents considerable difficulties. The objectives of this research are to analyze the effect of inflation and interest rates on conventional and Islamic banks in Afghanistan, identify potential differences between these two banking models, and provide insights for policymakers and practitioners. A mixed-methods approach is used in the research to analyze quantitative data and qualitatively examine the unique difficulties that banks in Afghanistan's economic atmosphere encounter. The findings contribute to the understanding of the relationship between interest rate, inflation rate, and the performance of both banking systems in Afghanistan. The paper concludes with recommendations for policymakers and banking institutions to enhance the stability and growth of the banking sector in Afghanistan. Interest is described as "a prefixed rate for use or borrowing of money" from an Islamic perspective. This "prefixed rate," known in Islamic economics as "riba," has been described as "something undesirable." Furthermore, by using the time series regression data technique on the annual data from 2003 to 2021, this research examines the effect of CPI inflation rate and interest rate of Banking in Afghanistan.

Keywords: inflation, Islamic banking, conventional banking, interest, Afghanistan, impact

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Authors: T. Bettaieb, S. Soufi, S. Arbaoui

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Stevia rebaudiana Bert. is a natural sweet plant. The leaves contain diterpene glycosides stevioside, rebaudiosides A-F, steviolbioside and dulcoside, which are responsible for its sweet taste and have commercial value all over the world as sugar substitute in foods and medicines. Stevia rebaudiana Bert. is sensitive temperature lower than 9°C. The possibility of its outdoor culture in Tunisian conditions demand genotypes tolerant to low temperatures. In order to evaluate the low temperature tolerance of eight genotypes of Stevia rebaudiana, the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalases (CAT) were measured. Before carrying out the analyses, three genotypes of Stevia were exposed for 1 month at a temperature regime of 18°C during the day and 7°C at night similar to winter conditions in Tunisia. In response to the stress generated by low temperature, antioxidant enzymes activity revealed on native gel and quantified by spectrophotometry showed variable levels according to their degree of tolerance to low temperatures.

Keywords: chilling tolerance, enzymatic activity, stevia rebaudiana bert, low thermal stress

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Authors: M. Dagim Yoseph, M. K. Savage, A. D. Jolly, C. J. Ebinger

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Whakaari/White Island has been the most active New Zealand volcano in the 21st century, producing small phreatic and phreatomagmatic eruptions, which are hard to predict. The most recent eruption occurred in 2019, tragically claiming the lives of 22 individuals and causing numerous injuries. We employed shear-wave splitting analyses to investigate variations in anisotropy between 2018 and 2020, during quiescence, unrest, and the eruption. We examined spatial and temporal variations in 3499 shear-wave splitting and 2656 V_p/V_s ratio measurements. Comparing shear-wave splitting parameters from similar earthquake paths across different times indicates that the observed temporal changes are unlikely to result from variations in earthquake paths through media with spatial variability. Instead, these changes may stem from variations in anisotropy over time, likely caused by changes in crack alignment due to stress or varying fluid content.

Keywords: background seismic waves, fast orientations, seismic anisotropy, V_p/V_s ratio

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Wang Jiankun

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This paper analyses how different educational backgrounds affect the mathematics performance of middle and high school students in terms of three dimensions: parental involvement, school teaching ability, and demographic variables and personal attributes of the student. Based on the analysis of Beijing High School Mathematics Competition in 2022, it was found that students from high level schools won significantly more awards than those from low level schools. In addition, a significant positive correlation (p<0.05) was identified between school level and students' mathematics performance. This study also confirms that parents' education level and family environment show a significant impact on the next generation’s mathematics learning performance. The findings suggest that interest and student’s habits, the family environment and the quality of teaching and learning at school are the main factors affecting the mathematics performance of middle and high school students.

Keywords: educational background, academic performance, middle and high school education, teenager

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Authors: Mai M. Khalaf, Hany M. Abd El-Lateef

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A new good application for the sol gel method is to improve the corrosion inhibition properties of carbon steel by the dip coating method of Nano TiO2 films and its modification with Poly Ethylene Glycol (PEG). The prepared coating samples were investigated by different techniques, X-ray diffraction, Scanning Electron Microscopy (SEM), transmission electron microscopy and Energy Dispersive X-ray Spectroscopy (EDAX). The corrosion inhibition performance of the blank carbon steel and prepared coatings samples were evaluated in 0.5 M H2SO4 by using Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization measurements. The results showed that corrosion resistance of carbon steel increases with increasing the number of coated layers of both nano–TiO2 films and its modification of PEG. SEM-EDAX analyses confirmed that the percentage atomic content of iron for the carbon steel in 0.5 M H2SO4 is 83% and after the deposition of the steel in nano TiO2 sol and that with PEG are 94.3% and 93.7% respectively.

Keywords: dip-coatings, corrosion protection, sol gel, TiO2 films, PEG

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Authors: Wojciech Gilewski, Anna Al Sabouni-Zawadzka, Jan Pelczynski

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This paper focuses on the analysis of tensile stresses perpendicular to the grain in simply supported beams with different geometry made of glued laminated timber. Two types of beams are considered: standard double-tapered beams described in Eurocode 5 and non-standard glulam beams with a flattened apex. The beams are analyzed using two methodology approaches: a code design verification method and a finite element method (FEM) in terms of the linear theory of elasticity with plane stress assumption. The performed analyses proved that both methodologies lead to consistent results in case of standard glulam beams and therefore, the FEM can be used in case of non-standard structures, which are not included in Eurocode 5. Moreover, the FE analysis of the glulam beam with a flattened apex showed that it can be treated as a structure with two apex zones.

Keywords: double-tapered beams, finite element analysis, glued laminated timber, perpendicular to grain stress

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: Fatima Mehmood, Khalid Farooq, Rabeea Bakhtawer

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For geotechnical engineers, one of the most important properties of soil to consider in various stability analyses is its shear strength which is governed by a number of factors. The objective of this research is to ascertain the effect of compaction and degree of saturation on the shear strength of fine-grained soil. For this purpose, three different dry densities such as in-situ, maximum standard proctor, and maximum modified proctor, were determined for the sandy clay soil. The soil samples were then prepared to keep dry density constant and varying degrees of saturation. These samples were tested for (UU) unconsolidated undrained shear strength in triaxial compression tests. The decrease in shear strength was observed with the decrease in density and increase in the saturation. The values of the angle of internal friction followed the same trend. However, the change in cohesion with the increase in saturation showed a different behavior, analogous to the compaction curve.

Keywords: compaction, degree of saturation, dry density, geotechnical investigation, laboratory testing, shear strength

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Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

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The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

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Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

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This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

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Authors: Wolfram Karg

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The Occupy-Movement came into in 2011 existence in the US as a reaction to one of the worst economic crisis since World War II. With cuts in benefits and social services, with people being evicted from their homes on the one hand and high bonuses granted to their managers of the very same companies, a strong feeling of injustice besieged people in the US and caused them to voice their anger peacefully in social media and on the streets. Due to the world-wide-web, users all around the world read about this movement and recognized the same injustice in their own countries, making Occupy a global movement. The vast array of topics covered by Occupy offers a unique chance to carry out a corpus-based discourse analysis based on the DIMEAN-Model. The focus on this paper is limited to two aspects of DIMEAN: intertextual references and the use of connectors in texts. Because the discourse is to a large extent carried out via posts in blogs, online-articles and comments, the paper also analyses, in how far modern (i.e. computer-based media) there is a correlation between the use of connectors in different communicative types used by the Occupy-Movement.

Keywords: discourse, new media, occupy, corpus analysis

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Sugene Kim

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The English articles are taught as a binary system based on nominal countability and definiteness. Despite the detailed rules of prescriptive grammar, it has been consistently reported in the literature that their correct usage is extremely difficult to master even for advanced learners of English as a second language (ESL) or a foreign language (EFL). Given that an English sentence (except for an imperative) cannot be constructed without a noun, which is always paired with one of the indefinite, definite, and zero articles; it is essential to understand specifically what causes ESL/EFL learners to misuse them. To that end, this study examined EFL learners’ article use employing a one-group pre–post-test design. Forty-three Korean college students received instruction on correct English article usage for two 75-minute classes employing the binary schema set up for the study. They also practiced in class how to apply the rules as instructed. Then, the participants were assigned a forced-choice elicitation task, which was also used as a pre-test administered three months prior to the instruction. Unlike the pre-test on which they only chose the correct article for each of the 40 items, the post-instruction task additionally asked them to give written accounts of their decision-making procedure to choose the article as they did. The participants’ performance was scored manually by checking whether the answer given is correct or incorrect, and their written comments were first categorized using thematic analysis and then ranked by frequency. The analyses of the performance on the two tasks and the written think-aloud data suggested that EFL learners exhibit fluctuation between specificity and definiteness, overgeneralizing the use of the definite article for almost all cataphoric references. It was apparent that they have trouble distinguishing from the two concepts possibly because the former is almost never introduced in the grammar books or classes designed for ESL/EFL learners. Particularly, most participants were found to be ignorant of the possibility of using nouns as [+specific, –definite]. Not surprisingly, the correct answer rates for such nouns averaged out at 33% and 46% on the pre- and post-tests, respectively, which narrowly reach half the overall mean correct answer rates of 65% on the pre-test and 81% on the post-test. In addition, correct article use for specific indefinites was most impermeable to instruction when compared with nouns used as [–specific, –definite] or [± specific, +definite]. Such findings underline the necessity for expanding the binary schema to a ternary form that incorporates the specificity feature, albeit not morphologically marked in the English language.

Keywords: countability, definiteness, English articles, specificity, ternary system

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: Armanul Hoque Shaon, Md Baizid Mahmud, Askander Nobi, Md. Raju Ahmed, Md. Jiabul Hoque

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In the Internet of Things (IoT), devices are linked to the internet through a wireless network, allowing them to collect and transmit data without the need for a human operator. Agriculture relies heavily on wireless sensors, which are a vital component of the Internet of Things (IoT). This kind of wireless sensor network monitors physical or environmental variables like temperatures, sound, vibration, pressure, or motion without relying on a central location or sink and collaboratively passes its data across the network to be analyzed. As the primary source of plant nutrients, the soil is critical to the agricultural industry's continued growth. We're excited about the prospect of developing an Internet of Things (IoT) solution. To arrange the network, the sink node collects groundwater levels and sends them to the Gateway, which centralizes the data and forwards it to the sensor nodes. The sink node gathers soil moisture data, transmits the mean to the Gateways, and then forwards it to the website for dissemination. The web server is in charge of storing and presenting the moisture in the soil data to the web application's users. Soil characteristics may be collected using a networked method that we developed to improve rice production. Paddy land is running out as the population of our nation grows. The success of this project will be dependent on the appropriate use of the existing land base.

Keywords: IoT based agriculture monitoring, intelligent irrigation, communicating network, rice production

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

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The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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Authors: Rajkumar N. Ingle

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In this paper, the existence of a solution of nonlinear functional random differential equations of the first order is proved under caratheodory condition. The study of the functional random differential equation has got importance in the random analysis of the dynamical systems of universal phenomena. Objectives: Nonlinear functional random differential equation is useful to the scientists, engineers, and mathematicians, who are engaged in N.F.R.D.E. analyzing a universal random phenomenon, govern by nonlinear random initial value problems of D.E. Applications of this in the theory of diffusion or heat conduction. Methodology: Using the concepts of probability theory, functional analysis, generally the existence theorems for the nonlinear F.R.D.E. are prove by using some tools such as fixed point theorem. The significance of the study: Our contribution will be the generalization of some well-known results in the theory of Nonlinear F.R.D.E.s. Further, it seems that our study will be useful to scientist, engineers, economists and mathematicians in their endeavors to analyses the nonlinear random problems of the universe in a better way.

Keywords: Random Fixed Point Theorem, functional random differential equation, N.F.R.D.E., universal random phenomenon

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Authors: Samar Aoujia, Théo Guérineaub, Rayan Zaitera, Evelyne Fargina, Younès Messaddeqb, Thierry Cardinala

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Two barium gallo-germanate glass series were elaborated to investigate the effect of the yttrium introduction on the glass physicochemical properties and crystallization behavior. One to twenty mol% of YO3/2 were either added into the glass matrix or substituted for gallium oxide. The glass structure was studied by Raman spectroscopy, and the thermal, optical, thermo-mechanical and physical properties are examined. The introduction of yttrium ions in both glass series increases the glass transition temperature, crystallization temperature, softening temperature, coefficient of linear thermal expansion and density. Through differential scanning calorimetry and X-ray diffraction analyses, it was found that competition occurs between the gallo-germanate zeolite-type phase and the yttrium-containing phase. From 13 mol% of YO3/2, the yttrium introduction impedes the formation of surface crystallization in these glasses.

Keywords: photonic, heavy-metal oxide, glass, crystallization

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Authors: Diana Katherine Gonzalez Galindo, David Rolando Suarez Mora

Abstract:

With this study, we used data mining as a new alternative of the solution to evaluate the comments of the customers in order to find a pattern that helps us to determine some behaviors to reduce the deactivation of the partners of the LEVEL app. In one of the greatest business created in the last times, the partners are being affected due to an internal process that compensates the customer for a bad experience, but these comments could be false towards the driver, that’s why we made an investigation to collect information to restructure this process, many partners have been disassociated due to this internal process and many of them refuse the comments given by the customer. The main methodology used in this case study is the observation, we recollect information in real time what gave us the opportunity to see the most common issues to get the most accurate solution. With this new process helped by data mining, we could get a prediction based on the behaviors of the customer and some basic data recollected such as the age, the gender, and others; this could help us in future to improve another process. This investigation gives more opportunities to the partner to keep his account active even if the customer writes a message through the app. The term is trying to avoid a recession of drivers in the future offering improving in the processes, at the same time we are in search of stablishing a strategy which benefits both the app’s managers and the associated driver.

Keywords: agent, driver, deactivation, rider

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

Abstract:

In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Hazel P. Atilano

Abstract:

In this age of AI-assisted teaching and learning, there seems to be a dearth of research literature on the linguistic analysis of English as a Second Language (ESL) student-generated paraphrased academic texts. This study sought to examine the lexico-semantic, morphosyntactic features of paraphrased academic texts generated by ESL students. Employing a descriptive qualitative design, specifically linguistic analysis, the study involved a total of 85 students from senior high school, college, and graduate school enrolled in research courses. Data collection consisted of a 60-minute real-time, on-site paraphrasing practice exercise using excerpts from discipline-specific literature reviews of 150 to 200 words. A focus group discussion (FGD) was conducted to probe into the challenges experienced by the participants. The writing exercise yielded a total of 516 paraphrase pairs. A total of 176 paraphrase units (PUs) and 340 non-paraphrase pairs (NPPs) were detected. Findings from the linguistic analysis of PUs reveal that the modifications made to the original texts are predominantly syntax-based (Diathesis Alterations and Coordination Changes) and a combination of Miscellaneous Changes (Change of Order, Change of Format, and Addition/Deletion). Results of the analysis of paraphrase extremes (PE) show that Identical Structures resulting from the use of synonymous substitutions, with no significant change in the structural features of the original, is the most frequently occurring instance of PE. The analysis of paraphrase errors reveals that synonymous substitutions resulting in identical structures are the most frequently occurring error that leads to PE. Another type of paraphrasing error involves semantic and content loss resulting from the deletion or addition of meaning-altering content. Three major themes emerged from the FGD: (1) The Challenge of Preserving Semantic Content and Fidelity; (2) The Best Words in the Best Order: Grappling with the Lexico-semantic and Morphosyntactic Demands of Paraphrasing; and (3) Contending with Limited Vocabulary, Poor Comprehension, and Lack of Practice. A pedagogical paradigm was designed based on the major findings of the study for a sustainable instructional intervention.

Keywords: academic text, lexico-semantic analysis, linguistic analysis, morphosyntactic analysis, paraphrasing

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